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arXiv 2024年

作者： Ito, Satoshi Sato, Yuki Endo, Naoya Ouchi, Shohei Graduate Program in Information Electrical and Electronic Systems Engineering Utsunomiya University Japan Department of Innovative Electrical and Electronic Engineering National Institute of Technology Oyama Japan

Simultaneous multislice (SMS) imaging is a one of the acceleration technique of magnetic resonance imaging. SMS requires accurate sensitivity distributions in the slice plane for each receiving coil. This requirement is difficult to satisfy in practice, limiting the applications of this imaging technique. Here, images are reconstructed by applying deep learning and amplitude modulation to each slice image. Simulation experiments show that image reconstruction can be achieved for both real- and complex-valued images. Image quality tends to decrease with increasing number of simultaneously acquired images. It is also shown that a larger difference in the phase modulation coefficients between slices tends to increase the quality of the reconstructed images. Simulation experiments and initial MR imaging experiments show promising results for this method. Copyright © 2024, The Authors. All rights reserved.

关键词： Holography

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PET Myocardial Flow Reserve Estimation from 4D-Coronary-CT using Deep Neural Network 46

PET Myocardial Flow Reserve Estimation from 4D-Coronary-CT u...

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46th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Shen, Chenxi Iwaguchi, Takafumi You, Shaodi Kawakubo, Masateru Nagao, Michinobu Kawasaki, Hiroshi Kyushu University Graduate School of Information Science and Electrical Engineering Fukuoka Japan Kyushu University Faculty of Information Science and Electrical Engineering Fukuoka Japan University of Amsterdam Informatics Institute Amsterdam Netherlands Kyushu University Faculty of Medical Sciences Department of Health Sciences Fukuoka Japan Tokyo Women's Medical University Department of Diagnostic Imaging & Nuclear Medicine Tokyo Japan

ISBN: (纸本)9798350371499

The myocardial flow reserve (MFR) index proves to be a highly effective means of assessing the severity of myocardial ischemic disease. An MFR value below two commonly indicates impaired coronary artery perfusion function. Nevertheless, the measurement of MFR using the NH3-positron emission tomography (NH3-PET) method is both invasive and time-consuming. In order to alleviate the burden on both patients and doctors, we aim to achieve accurate estimation of MFR through a coronary computed tomography angiography image processing method. In this paper, we propose 2 methods: one is estimation method of MFR using i) coronary flow index (CFI) with multiple linear regression (MLR) and the other one is ii) vertical-time (VT) image with fully connected network (FCN) and convolutional neural network (CNN). We evaluate the performance between the observed and estimated MFR values with the Pearson correlation coefficient. The results show that LAD = 0.31, LCX = 0.19, and RCA = -0.21 in MLR method;LAD = 0.19, LCX =-0.37, and RCA = 0.23 in FCN and LAD = 0.34, LCX = 0.44 and RCA = 0.37 in CNN. The results exhibit superior performance based on VT images-based method compared to the CFI-based method, which show that VT images method is *** relevance- MFR is a crucial indicator in the clinical field of cardiovascular diseases, aiding in the early diagnosis, risk assessment, treatment monitoring, and prognosis evaluation of cardiac conditions. Nevertheless, the measurement of MFR using the NH3-PET method is both invasive and time-consuming. Our results show that estimating the MFR through VT images is a promising method. © 2024 IEEE.

关键词： Computerized tomography

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DEEP LEARNING-BASED CHANNEL ESTIMATION FOR RIS-ASSISTED UAV-ENABLED WIRELESS COMMUNICATIONS SYSTEM

DEEP LEARNING-BASED CHANNEL ESTIMATION FOR RIS-ASSISTED UAV-...

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2023 International Conference on Innovation, Communication and engineering, ICICE 2023

作者： Tesfaw, Belayneh A. Lin, Hsin-Piao Tarekegn, Getaneh B. Juang, Rong-Terng Jeng, Shiann-Shiun Department of International Graduate Program in Electrical Engineering and Computer Science National Taipei University of Technology Taipei Taiwan Institute of Aerospace and System Engineering National Taipei University of Technology Taipei10608 Taiwan Department of Electrical and Computer Engineering National Yang-Ming Chiao Tung University Hsinchu30010 Taiwan Department of Electrical Engineering National Dong Hwa University Hualien Taiwan

ISBN: (纸本)9781839539954

Wireless communication via unmanned aerial vehicles (UAVs) has drawn a great deal of attention due to its flexibility in establishing line-of-sight (LoS) communications. However, in complex urban and dynamic environments, the movement of UAVs can be blocked by trees and high-rise buildings that obstruct directional paths. This problem can be effectively addressed by employing reconfigurable intelligent surfaces (RIS). To achieve this goal, accurate channel estimation in RIS-assisted UAV-enabled wireless communications is crucial. This paper proposes an accurate channel estimation model using long short-term memory (LSTM) for a multi-user RIS-assisted UAV-enabled wireless communications system. Simulation results showed that LSTM can effectively improve the channel estimation performance of RIS-assisted UAV-enabled wireless communications. © The Institution of engineering & Technology 2023.

关键词： Channel estimation

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Purcell Enhancement of a Single T Center Coupled to a Silicon Nanophotonic Cavity

Purcell Enhancement of a Single T Center Coupled to a Silico...

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CLEO: Fundamental Science, CLEO:FS 2024 - Part of Conference on Lasers and Electro-Optics, CLEO 2024

作者： Felix-Rendon, Ulises Johnston, Adam Wong, Yu-En Chen, Songtao Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States Applied Physics Graduate Program Smalley-Curl Institute Rice University HoustonTX77005 United States Smalley-Curl Institute Rice University HoustonTX77005 United States

We demonstrate Purcell enhancement of a single T center integrated in a silicon photonic crystal cavity, increasing the fluorescence decay rate by a factor of 6.89 and achieving a photon outcoupling rate of 73.3 kHz. ... 详细信息

ISBN: (纸本)9781957171395

关键词： Silicon photonics

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Scene Text Recognition Models Explainability Using Local Features

Scene Text Recognition Models Explainability Using Local Fea...

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IEEE International Conference on Image Processing

作者： Mark Vincent Ty Rowel Atienza Electrical and Electronics Engineering Institute University of the Philippines AI Graduate Program University of the Philippines

Explainable AI (XAI) is the study on how humans can be able to understand the cause of a model’s prediction. In this work, the problem of interest is Scene Text Recognition (STR) Explainability, using XAI to understand the cause of an STR model’s prediction. Recent XAI literatures on STR only provide a simple analysis and do not fully explore other XAI methods. In this study, we specifically work on data explainability frameworks, called attribution-based methods, that explains the important parts of an input data in deep learning models. However, integrating them into STR produces inconsistent and ineffective explanations, because they only explain the model in the global context. To solve this problem, we propose a new method, STRExp, to take into consideration the local explanations, i.e. the individual character prediction explanations. This is then benchmarked across different attribution-based methods on different STR datasets and evaluated across different STR models.

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Utilizing Battery Energy Storage Systems to Enhance the Integration of Photovoltaic Systems for Damping Oscillations

Utilizing Battery Energy Storage Systems to Enhance the Inte...

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IEEE Southeastcon

作者： Ilham Akbar Ariesa Budi Zakaria Mayur Basu Eduard Muliadi Suwarno Nanang Hariyanto Graduate Program PLN-ITB PLN Corporate University Auburn USA Electrical and Computer Engineering Auburn University Auburn USA School of Electrical Engineering and Informatics Institut Teknologi Bandung (ITB) Bandung Indonesia

As the integration of Variable Renewable Energy (VRE) generators into power systems increases, there is a potential decrease in overall system reliability, particularly in terms of stability. This research suggests the integration of a Battery Energy Storage System (BESS) into a power system with Variable Renewable Energy sources, such as a utility-scale Photovoltaic (PV) plant, to accelerate the damping of post-fault oscillations following a short-circuit disturbance. The objective is for a Power Oscillation Damping (POD) within the PV plant to address post-fault oscillations within a specific timeframe. The POD in the PV plant is designed to supply additional active and reactive power, responding to the system's demands after a disturbance. The addition of BESS to the system is anticipated to enhance the time required for the system to achieve a stable state, resulting in quicker system stabilization. Simulations conducted through PSCAD software can effectively depict the post-fault conditions of short-circuit disturbances, considering the impact of the integrated BESS.

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Analysis of Loss Tangent in Current Transformers Using the Finite Element Method 23

Analysis of Loss Tangent in Current Transformers Using the F...

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23rd International Symposium on High Voltage engineering, ISH 2023

作者： Leite Neto, Antonio F. Guedes, Edson G. Vilar, Pablo B. Lira, George R.S. Andrade, Filipe L.M. Melo, João Victor J. Junior, Almir C.S. Marotti, Ana C.F. Costa, André I. Souza, João Paulo A. Electrical Engineering Graduate Program Federal University of Campina Grande Campina Grande Brazil Department of Electrical Engineering Federal University of Campina Grande Campina Grande Brazil Department of Electrical Engineering Federal Institute of Paraiba Patos Brazil Eletrobras Furnas Electric Power Furnas Rio de Janeiro Brazil Concert Concert Technologies Belo Horizonte Brazil

ISBN: (纸本)9781839539954

Failures in Current Transformers (CTs) can have a significant financial impact on utilities, causing revenue loss, service interruptions, and even damage to nearby equipment. To minimize the effects of CT degradation on the electrical system, predictive techniques and continuous monitoring are essential. One such tool that can aid in the supervision and diagnosis of equipment in service is the loss tangent. This parameter is directly related to the aging and degradation of electrical insulation, making it a useful indicator of possible failures in CTs. Therefore, this work aims to perform computer simulations using the finite element method (FEM) to simulate the effect of oil and paper degradation on the loss tangent values of a 230 kV current transformer. To achieve this, the COMSOL Multiphysics® software was used to verify the loss tangent as a function of the conductivity of parameters correlated to the CT dielectric. The results of the simulations show that the degradation of oil and paper substantially increases the value of the loss tangent. Additionally, it was found that the simultaneous or individual degradation of oil and paper have different effects on the loss tangent values obtained. The findings of this study demonstrate the usefulness of loss tangent as a tool for the diagnosis and supervision of electrical equipment in service. © The Institution of engineering & Technology 2023.

关键词： Distribution transformers

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Reducing Dependency on Imported Electricity: Utilizing Renewable Energy and Minimizing Fossil Fuel Power Plant Operations in West Kalimantan

Reducing Dependency on Imported Electricity: Utilizing Renew...

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IEEE Energy Conversion Congress and Exposition, ECCE

作者： Ilham Akbar Ariesa Budi Zakaria Eduard Muljadi Suwarno Nanang Hariyanto Graduate Program PLN-ITB PLN Corporate University Auburn USA Electrical and Computer Engineering Auburn University Auburn USA School of Electrical Engineering and Informatics Institut Teknologi Bandung (ITB) Bandung Indonesia

ISBN: (数字)9798350376067

ISBN: (纸本)9798350376074

This paper discusses West Kalimantan's dependency on imported electricity and fossil fuels and advocates for integrating renewable energy sources, especially solar power. With abundant solar resources and its equatorial location, West Kalimantan presents a significant solar PV generation opportunity. However, its dependence on imported electricity from the ASEAN Grid initiative poses risks to energy security. By promoting solar power as an alternative energy source and reducing reliance on fossil fuels, the paper aims to improve energy independence and sustainability. Integrating solar PV requires assessing frequency stability to ensure system resilience. Moreover, the interconnection between the two grids enhances system resilience and facilitates renewable energy integration. In summary, integrating solar PV power plants into the West Kalimantan system aims to decrease dependence on electricity imports from Sarawak while preserving the system's frequency stability.

关键词： Photovoltaic systems Renewable energy sources Fault tolerance Electricity Power system stability Fossil fuels Security Sustainable development Thermal stability Research and development

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Power Oscillation Damping of a Wind Turbine Generation with Battery Energy to Smoothen Power System Stability

Power Oscillation Damping of a Wind Turbine Generation with ...

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IEEE Southeastcon

作者： Ariesa Budi Zakaria Ilham Akbar Mayur Basu Eduard Muljadi Suwano Nanang Hariyanto Graduate Program PLN-ITB PLN Corporate University Auburn USA Electrical and Computer Engineering Auburn University Auburn USA School of Electrical Engineering and Informatics Institut Teknologi Bandung (ITB) Bandung Indonesia

Integrating wind turbine generation (WTG) into the power grid presents challenges due to their variable and unpredictable output, creating instability. The intermittent nature of wind power and the reduced inertia of wind turbines pose significant challenges to maintaining power system stability, especially during grid faults and transient events. Intermittency can impact the electrical grid's stability and requires additional grid balancing and energy storage measures. This study proposes a Power Oscillation Damping (POD) control scheme integrated with battery energy to enhance WTG stability following grid faults. The proposed scheme combines a POD controller for WTG and a battery controller, demonstrating faster oscillation damping than a WTG without batteries. During damping control, the scheme prioritizes active power control of POD, utilizing the wind turbine's kinetic energy. Simultaneously, the reactive power control of POD adjusts based on the synchronous generator's rotational speed to maintain voltage stability. Feedback for both control loops is derived from the nearest synchronous generator, ensuring coordinated and responsive control. Adding a battery into the control scheme helps to smooth out power fluctuations and enhance stability. Therefore, it is possible to compensate for the intermittency of wind power and voltage drop after short-circuit events through various measures, such as advanced control systems and battery power. The effectiveness of this proposed control scheme, with the added integration of Battery Energy, is validated through the PSCAD simulator involving a short-circuit fault in a two-area power system. Results demonstrate a notable improvement in power system stability, particularly after grid faults.

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Multi-task Learning Graph Neural Networks for Cancer Prognosis Prediction with Genomic Data

Multi-task Learning Graph Neural Networks for Cancer Prognos...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Tsung-Wei Lin Sofia Ormazabal Arriagada Che Lin Graduate Institute of Communication Engineering National Taiwan University (NTU) Taiwan International Graduate Program AIoT NTU Research Center for Information Technology Innovation Academia Sinica Department of Electrical Engineering NTU Center for Advanced Computing and Imaging in Biomedicine NTU Smart Medicine and Health Informatics Program NTU

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

Providing robust prognosis predictions for cancers with limited data samples remains a challenge for precision oncology. In this study, we propose a novel approach that combines multi-task learning (MTL) and graph neural networks (GNNs) to address this issue. By representing gene-gene interactions as a graph network, our approach leverages multi-task learning to effectively capture the relationships of genes relevant to the oncogenesis and progression of breast, lung, and colon cancer. We demonstrate that our approach improves the cancer prognosis prediction for cancers with fewer samples, such as colon adenocarcinoma, by leveraging the shared gene-gene interactions across different cancer types, obtaining increases in the area under the precision-recall curve (AUPRC) of 24%. Our work contributes to the field of smart healthcare by demonstrating the potential of MTL and GNNs for enhancing cancer prognosis prediction, even with limited data samples.

关键词： Lungs Genomics Medical services Colorectal cancer Breast Multitasking Oncology Graph neural networks Prognostics and health management Cancer

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